Filtering walking actigraphy data in children with unilateral cerebral palsy: A preliminary study.

This study aimed to determine whether filtering out walking-related actigraphy data improves the reliability and accuracy of real-world upper extremity activity assessment in children with unilateral cerebral palsy. Twenty-two children aged 4-12 years diagnosed with unilateral cerebral palsy were included in this study, which was drawn from a two-phase randomized controlled trial conducted from July 2021 to December 2022. Data were collected from a tertiary hospital in Seoul, Republic of Korea. Participants were monitored using tri-axial accelerometers on both wrists across three time points (namely, T0, T1, and T2) over 3 days; interventions were used between each time point. Concurrently, an in-laboratory study focusing on walking and bimanual tasks was conducted with four participants. Data filtration resulted in a reduction of 8.20% in total data entry. With respect to reliability assessment, the intra-class correlation coefficients indicated enhanced consistency after filtration, with increased values for both the affected and less-affected sides. Before filtration, the magnitude counts for both sides showed varying tendencies, depending on the time points; however, they presented a consistent and stable trend after filtration. The findings of this research underscore the importance of accurately interpreting actigraphy measurements in children with unilateral cerebral palsy for targeted upper limb intervention by filtering walking-induced data.

Stroke walking and balance characteristics via principal component analysis.

Balance impairment is associated gait dysfunction with several quantitative spatiotemporal gait parameters in patients with stroke. However, the link between balance impairments and joint kinematics during walking remains unclear. Clinical assessments and gait measurements using motion analysis system was conducted in 44 stroke patients. This study utilised principal component analysis to identify key joint kinematics characteristics of patients with stroke during walking using average joint angles of pelvis and bilateral lower limbs in every gait-cycle percentile related to balance impairments. Reconstructed kinematics showed the differences in joint kinematics in both paretic and nonparetic lower limbs that can be distinguished by balance impairment, particularly in the sagittal planes during swing phase. The impaired balance group exhibited greater joint variability in both the paretic and nonparetic limbs in the sagittal plane during entire gait phase and during terminal swing phase respectively compared with those with high balance scores. This study provides a more comprehensive understanding of stroke hemiparesis gait patterns and suggests considering both nonparetic and paretic limb function, as well as bilateral coordination in clinical practice. Principal component analysis can be a useful assessment tool to distinguish differences in balance impairment and dynamic symmetry during gait in patients with stroke.

Characteristic Changes of the Stance-Phase Plantar Pressure Curve When Walking Uphill and Downhill: Cross-Sectional Study.

BACKGROUND: Monitoring of gait patterns by insoles is popular to study behavior and activity in the daily life of people and throughout the rehabilitation process of patients. Live data analyses may improve personalized prevention and treatment regimens, as well as rehabilitation. The M-shaped plantar pressure curve during the stance phase is mainly defined by the loading and unloading slope, 2 maxima, 1 minimum, as well as the force during defined periods. When monitoring gait continuously, walking uphill or downhill could affect this curve in characteristic ways. OBJECTIVE: For walking on a slope, typical changes in the stance phase curve measured by insoles were hypothesized. METHODS: In total, 40 healthy participants of both sexes were fitted with individually calibrated insoles with 16 pressure sensors each and a recording frequency of 100 Hz. Participants walked on a treadmill at 4 km/h for 1 minute in each of the following slopes: -20%, -15%, -10%, -5%, 0%, 5%, 10%, 15%, and 20%. Raw data were exported for analyses. A custom-developed data platform was used for data processing and parameter calculation, including step detection, data transformation, and normalization for time by natural cubic spline interpolation and force (proportion of body weight). To identify the time-axis positions of the desired maxima and minimum among the available extremum candidates in each step, a Gaussian filter was applied (σ=3, kernel size 7). Inconclusive extremum candidates were further processed by screening for time plausibility, maximum or minimum pool filtering, and monotony. Several parameters that describe the curve trajectory were computed for each step. The normal distribution of data was tested by the Kolmogorov-Smirnov and Shapiro-Wilk tests. RESULTS: Data were normally distributed. An analysis of variance with the gait parameters as dependent and slope as independent variables revealed significant changes related to the slope for the following parameters of the stance phase curve: the mean force during loading and unloading, the 2 maxima and the minimum, as well as the loading and unloading slope (all P<.001). A simultaneous increase in the loading slope, the first maximum and the mean loading force combined with a decrease in the mean unloading force, the second maximum, and the unloading slope is characteristic for downhill walking. The opposite represents uphill walking. The minimum had its peak at horizontal walking and values dropped when walking uphill and downhill alike. It is therefore not a suitable parameter to distinguish between uphill and downhill walking. CONCLUSIONS: While patient-related factors, such as anthropometrics, injury, or disease shape the stance phase curve on a longer-term scale, walking on slopes leads to temporary and characteristic short-term changes in the curve trajectory.

A patient-centered 'test-drive' strategy for ankle-foot orthosis prescription: Protocol for a randomized participant-blinded trial.

BACKGROUND: Ankle-foot orthoses (AFOs) are commonly used to overcome mobility limitations related to lower limb musculoskeletal injury. Despite a multitude of AFOs to choose from, there is scant evidence to guide AFO prescription and limited opportunities for AFO users to provide experiential input during the process. To address these limitations in the current prescription process, this study evaluates a novel, user-centered and personalized 'test-drive' strategy using a robotic exoskeleton ('AFO emulator') to emulate commercial AFO mechanical properties (i.e., stiffness). The study will determine if brief, in-lab trials (with emulated or actual AFOs) can predict longer term preference, satisfaction, and mobility outcomes after community trials (with the actual AFOs). Secondarily, it will compare the in-lab experience of walking between actual vs. emulated AFOs. METHODS AND ANALYSIS: In this participant-blinded, randomized crossover study we will recruit up to fifty-eight individuals with lower limb musculoskeletal injuries who currently use an AFO. Participants will walk on a treadmill with three actual AFOs and corresponding emulated AFOs for the "in-lab" assessments. For the community trial assessment, participants will wear each of the actual AFOs for a two-week period during activities of daily living. Performance-based and user-reported measures of preference and mobility will be compared between short- and long-term trials (i.e., in-lab vs. two-week community trials), and between in-lab trials (emulated vs. actual AFOs). TRIAL REGISTRATION: The study was prospectively registered at www.clininicaltrials.gov (Clinical Trials Study ID: NCT06113159). Date: November 1st 2023. https://classic.clinicaltrials.gov/ct2/show/NCT06113159.

A comprehensive dataset on biomechanics and motor control during human walking with discrete mechanical perturbations.

Background: Humans have a remarkable capability to maintain balance while walking. There is, however, a lack of publicly available research data on reactive responses to destabilizing perturbations during gait. Methods: Here, we share a comprehensive dataset collected from 10 participants who experienced random perturbations while walking on an instrumented treadmill. Each participant performed six 5-min walking trials at a rate of 1.2 m/s, during which rapid belt speed perturbations could occur during the participant's stance phase. Each gait cycle had a 17% probability of being perturbed. The perturbations consisted of an increase of belt speed by 0.75 m/s, delivered with equal probability at 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80% of the stance phase. Data were recorded using motion capture with 25 markers, eight inertial measurement units (IMUs), and electromyography (EMG) from the tibialis anterior (TA), soleus (SOL), lateral gastrocnemius (LG), rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), and gluteus maximus (GM). The full protocol is described in detail. Results: We provide marker trajectories, force plate data, EMG data, and belt speed information for all trials and participants. IMU data is provided for most participants. This data can be useful for identifying neural feedback control in human gait, biologically inspired control systems for robots, and the development of clinical applications.

Effects of walking speeds on lower extremity kinematic synergy in toe vertical position control: An experimental study.

BACKGROUND: This study aimed to investigate whether lower limb joints mutually compensate for each other, resulting in motor synergy that suppresses toe vertical position fluctuation, and whether walking speeds affect lower limb synergy. METHODS: Seventeen male university students walked at slow (0.85 ±â€…0.04 m/s), medium (1.43 ±â€…0.05 m/s) and fast (1.99 ±â€…0.06 m/s) speeds on a 15-m walkway while lower limb kinematic data were collected. Uncontrolled manifold analysis was used to quantify the strength of synergy. Two-way (speed × phase) repeated-measures analysis of variance was used to analyze all dependent variables. RESULTS: A significant speed-by-phase interaction was observed in the synergy index (SI) (P  < .001). At slow walking speeds, subjects had greater SI during mid-swing (P  < .001), while at fast walking speeds, they had greater SI during early-swing (P  < .001). During the entire swing phase, fast walking exhibited lower SI values than medium (P  = .005) and slow walking (P  = .027). CONCLUSION: Kinematic synergy plays a crucial role in controlling toe vertical position during the swing phase, and fast walking exhibits less synergy than medium and slow walking. These findings contribute to a better understanding of the role of kinematic synergy in gait stability and have implications for the development of interventions aimed at improving gait stability and reducing the risk of falls.

Human Activity Recognition in a Free-Living Environment Using an Ear-Worn Motion Sensor.

Human activity recognition (HAR) technology enables continuous behavior monitoring, which is particularly valuable in healthcare. This study investigates the viability of using an ear-worn motion sensor for classifying daily activities, including lying, sitting/standing, walking, ascending stairs, descending stairs, and running. Fifty healthy participants (between 20 and 47 years old) engaged in these activities while under monitoring. Various machine learning algorithms, ranging from interpretable shallow models to state-of-the-art deep learning approaches designed for HAR (i.e., DeepConvLSTM and ConvTransformer), were employed for classification. The results demonstrate the ear sensor's efficacy, with deep learning models achieving a 98% accuracy rate of classification. The obtained classification models are agnostic regarding which ear the sensor is worn and robust against moderate variations in sensor orientation (e.g., due to differences in auricle anatomy), meaning no initial calibration of the sensor orientation is required. The study underscores the ear's efficacy as a suitable site for monitoring human daily activity and suggests its potential for combining HAR with in-ear vital sign monitoring. This approach offers a practical method for comprehensive health monitoring by integrating sensors in a single anatomical location. This integration facilitates individualized health assessments, with potential applications in tele-monitoring, personalized health insights, and optimizing athletic training regimes.

Implementation and Evaluation of Walk-in-Place Using a Low-Cost Motion-Capture Device for Virtual Reality Applications.

Virtual reality (VR) is used in many fields, including entertainment, education, training, and healthcare, because it allows users to experience challenging and dangerous situations that may be impossible in real life. Advances in head-mounted display technology have enhanced visual immersion, offering content that closely resembles reality. However, several factors can reduce VR immersion, particularly issues with the interactions in the virtual world, such as locomotion. Additionally, the development of locomotion technology is occurring at a moderate pace. Continuous research is being conducted using hardware such as treadmills, and motion tracking using depth cameras, but they are costly and space-intensive. This paper presents a walk-in-place (WIP) algorithm that uses Mocopi, a low-cost motion-capture device, to track user movements in real time. Additionally, its feasibility for VR applications was evaluated by comparing its performance with that of a treadmill using the absolute trajectory error metric and survey data collected from human participants. The proposed WIP algorithm with low-cost Mocopi exhibited performance similar to that of the high-cost treadmill, with significantly positive results for spatial awareness. This study is expected to contribute to solving the issue of spatial constraints when experiencing infinite virtual spaces.

Brain Networks Modulation during Simple and Complex Gait: A "Mobile Brain/Body Imaging" Study.

Walking encompasses a complex interplay of neuromuscular coordination and cognitive processes. Disruptions in gait can impact personal independence and quality of life, especially among the elderly and neurodegenerative patients. While traditional biomechanical analyses and neuroimaging techniques have contributed to understanding gait control, they often lack the temporal resolution needed for rapid neural dynamics. This study employs a mobile brain/body imaging (MoBI) platform with high-density electroencephalography (hd-EEG) to explore event-related desynchronization and synchronization (ERD/ERS) during overground walking. Simultaneous to hdEEG, we recorded gait spatiotemporal parameters. Participants were asked to walk under usual walking and dual-task walking conditions. For data analysis, we extracted ERD/ERS in α, ß, and γ bands from 17 selected regions of interest encompassing not only the sensorimotor cerebral network but also the cognitive and affective networks. A correlation analysis was performed between gait parameters and ERD/ERS intensities in different networks in the different phases of gait. Results showed that ERD/ERS modulations across gait phases in the α and ß bands extended beyond the sensorimotor network, over the cognitive and limbic networks, and were more prominent in all networks during dual tasks with respect to usual walking. Correlation analyses showed that a stronger α ERS in the initial double-support phases correlates with shorter step length, emphasizing the role of attention in motor control. Additionally, ß ERD/ERS in affective and cognitive networks during dual-task walking correlated with dual-task gait performance, suggesting compensatory mechanisms in complex tasks. This study advances our understanding of neural dynamics during overground walking, emphasizing the multidimensional nature of gait control involving cognitive and affective networks.

Cross-sectional associations between temporal patterns and composition of upright and stepping events with physical function in midlife: Insights from the 1970 British Cohort Study.

INTRODUCTION: Age-related decline in physical functioning has significant implications for health in later life but declines begin earlier in midlife. Physical activity (PA) volume is associated with physical function, but the importance of the pattern in which PA is accumulated is unclear. This study investigates associations between patterns of PA accumulation, including the composition, variation, and temporal distribution of upright and stepping events, with physical function in midlife. METHODS: Participants (n = 4378) from the 1970 British Cohort Study wore an activPAL3 accelerometer on the thigh for 7 consecutive days. Exposure measures included a suite of metrics describing the frequency, duration, and composition of upright events, as well as the duration and volume (total steps) of stepping events. In addition, patterns of accumulation of upright and sedentary events were examined including how fragmented/transient they were (upright-to-sedentary transition probability [USTP]) and their burstiness (the tendency for events to be clustered together followed by longer interevent times). Physical function outcomes included grip strength (GS), balance, and SF-36 physical functioning subscale (SF-36pf). Cross-sectional analyses included multivariable linear regression models to assess associations, adjusting for covariates including overall PA volume (mean daily step count). RESULTS: Higher upright event burstiness was associated with higher GS, and higher USTP was associated with lower GS. Duration and step volume of stepping events were positively associated with SF-36pf in females. Step-weighted cadence was positively associated with SF-36pf and balance. Contradictory findings were also present (e.g., more transient stepping events were associated with better GS) particularly for GS in males. Inconsistencies between sexes were observed across some associations. CONCLUSION: Our study reveals that diverse patterns of PA accumulation exhibit distinct associations with various measures of physical function in midlife, irrespective of the overall volume. Contradictory findings and inconsistency between sexes warrant further investigation. Patterns of PA accumulation, in addition to volume, should be considered in future PA research. Longitudinal studies are required to determine whether a given volume of activity accumulated in different patterns, impacts associations between PA and health outcomes.

Back geometry and mobility function changes in cerebral palsy children after backward walking training: arandomized controlled trial.

AIM: To compare the effects of backward (BW) and forward (FW) walking training on back geometry and mobility function in children with hemiparetic cerebral palsy (CP). METHODS: Fifty-five children with hemiparetic CP participated in this study. They were randomly assigned into two groups. For 12 weeks, both groups got a conventional physical therapy program three days/week. Groups A and B got a specifically developed FW walking training (25 minutes/session) and a specially designed BW walking training (25 minutes/session), respectively. RESULTS: The trunk imbalance, lateral deviation, pelvic tilting, pelvic torsion, surface motion, and dynamic gait index of group B improved significantly more than group A (p < .05). Both groups showed significant improvements in all measured variables (p < .05). CONCLUSION: BW walking training might be considered as an effective therapy modality for improving back geometry and mobility function in hemiparetic CP children compared with FW walking training combined with a typical program.

Determination of dynamic air gap thickness and analysis of its relationship with firefighters' joint movement.

Objectives. The purpose of this study was to calculate the dynamic air gap thickness between the human body and the turnout gear. Relationships between the air gap thickness and joint range of motion (ROM) were also explored. Methods. The air gap thickness and joint ROM of 12 male firefighters walking in a control condition with no self-contained breathing apparatus (SCBA) and three varying-strapped SCBAs were measured using three-dimensional (3D) body scanning and 3D inertial motion capture. The interpolation technique was employed to predict the air gap thickness curve during walking. The dynamic air gap thickness was compared with the joint ROM to see how they relate to the location and percentage of movement restriction. Results. During the walking, the air gap fluctuated as a sine curve. Carrying SCBA reduced the air gap thickness at the trunk most (F = 11.17, p < 0.001, η2 = 0.63), and adjusting the shoulder strap length altered the air gap distribution at the trunk. The reduced air gap at the pelvis caused an incremental restriction on pelvis rotation. Conclusions. A compatibility design of the shoulder strap and hip belt in SCBA with the turnout jacket is suggested.

SensAA-Design and Verification of a Cloud-Based Wearable Biomechanical Data Acquisition System.

Exoskeletons designed to assist patients with activities of daily living are becoming increasingly popular, but still are subject to research. In order to gather requirements for the design of such systems, long-term gait observation of the patients over the course of multiple days in an environment of daily living are required. In this paper a wearable all-in-one data acquisition system for collecting and storing biomechanical data in everyday life is proposed. The system is designed to be cost efficient and easy to use, using off-the-shelf components and a cloud server system for centralized data storage. The measurement accuracy of the system was verified, by measuring the angle of the human knee joint at walking speeds between 3 and 12 km/h in reference to an optical motion analysis system. The acquired data were uploaded to a cloud database via a smartphone application. Verification results showed that the proposed toolchain works as desired. The system reached an RMSE from 2.9° to 8°, which is below that of most comparable systems. The system provides a powerful, scalable platform for collecting and processing biomechanical data, which can help to automize the generation of an extensive database for human kinematics.

Dynamic Stability, Symmetry, and Smoothness of Gait in People with Neurological Health Conditions.

Neurological disorders such as stroke, Parkinson's disease (PD), and severe traumatic brain injury (sTBI) are leading global causes of disability and mortality. This study aimed to assess the ability to walk of patients with sTBI, stroke, and PD, identifying the differences in dynamic postural stability, symmetry, and smoothness during various dynamic motor tasks. Sixty people with neurological disorders and 20 healthy participants were recruited. Inertial measurement unit (IMU) sensors were employed to measure spatiotemporal parameters and gait quality indices during different motor tasks. The Mini-BESTest, Berg Balance Scale, and Dynamic Gait Index Scoring were also used to evaluate balance and gait. People with stroke exhibited the most compromised biomechanical patterns, with lower walking speed, increased stride duration, and decreased stride frequency. They also showed higher upper body instability and greater variability in gait stability indices, as well as less gait symmetry and smoothness. PD and sTBI patients displayed significantly different temporal parameters and differences in stability parameters only at the pelvis level and in the smoothness index during both linear and curved paths. This study provides a biomechanical characterization of dynamic stability, symmetry, and smoothness in people with stroke, sTBI, and PD using an IMU-based ecological assessment.

Ubiquitous Gait Analysis through Footstep-Induced Floor Vibrations.

Quantitative analysis of human gait is critical for the early discovery, progressive tracking, and rehabilitation of neurological and musculoskeletal disorders, such as Parkinson's disease, stroke, and cerebral palsy. Gait analysis typically involves estimating gait characteristics, such as spatiotemporal gait parameters and gait health indicators (e.g., step time, length, symmetry, and balance). Traditional methods of gait analysis involve the use of cameras, wearables, and force plates but are limited in operational requirements when applied in daily life, such as direct line-of-sight, carrying devices, and dense deployment. This paper introduces a novel approach for gait analysis by passively sensing floor vibrations generated by human footsteps using vibration sensors mounted on the floor surface. Our approach is low-cost, non-intrusive, and perceived as privacy-friendly, making it suitable for continuous gait health monitoring in daily life. Our algorithm estimates various gait parameters that are used as standard metrics in medical practices, including temporal parameters (step time, stride time, stance time, swing time, double-support time, and single-support time), spatial parameters (step length, width, angle, and stride length), and extracts gait health indicators (cadence/walking speed, left-right symmetry, gait balance, and initial contact types). The main challenge we addressed in this paper is the effect of different floor types on the resultant vibrations. We develop floor-adaptive algorithms to extract features that are generalizable to various practical settings, including homes, hospitals, and eldercare facilities. We evaluate our approach through real-world walking experiments with 20 adults with 12,231 labeled gait cycles across concrete and wooden floors. Our results show 90.5% (RMSE 0.08s), 71.3% (RMSE 0.38m), and 92.3% (RMSPE 7.7%) accuracy in estimating temporal, spatial parameters, and gait health indicators, respectively.

Experimental Evaluation of Pedestrian-Induced Multiaxial Gait Loads on Footbridges: Effects of the Structure-to-Human Interaction by Lateral Vibrating Platforms.

The introduction of resistant and lightweight materials in the construction industry has led to civil structures being vulnerable to excessive vibrations, particularly in footbridges exposed to human-induced gait loads. This interaction, known as Human-Structure Interaction (HSI), involves a complex interplay between structural vibrations and gait loads. Despite extensive research on HSI, the simultaneous effects of lateral structural vibrations with fundamental frequencies close to human gait frequency (around 1.0 Hz) and wide amplitudes (over 30.0 mm) remain inadequately understood, posing a contemporary structural challenge highlighted by incidents in iconic bridges like the Millennium Bridge in London, Solferino Bridge in Paris, and Premier Bridge in Cali, Colombia. This paper focuses on the experimental exploration of Structure-to-Human Interaction (S2HI) effects using the Human-Structure Interaction Multi-Axial Test Framework (HSI-MTF). The framework enables the simultaneous measurement of vertical and lateral loads induced by human gait on surfaces with diverse frequency ranges and wide-amplitude lateral harmonic motions. The study involved seven test subjects, evaluating gait loads on rigid and harmonic lateral surfaces with displacements ranging from 5.0 to 50.0 mm and frequency content from 0.70 to 1.30 Hz. A low-cost vision-based motion capture system with smartphones analyzed the support (Tsu) and swing (Tsw) periods of human gait. Results indicated substantial differences in Tsu and Tsw on lateral harmonic protocols, reaching up to 96.53% and 58.15%, respectively, compared to rigid surfaces. Normalized lateral loads (LL) relative to the subject's weight (W0) exhibited a linear growth proportional to lateral excitation frequency, with increased proportionality constants linked to higher vibration amplitudes. Linear regressions yielded an average R2 of 0.815. Regarding normalized vertical load (LV) with respect to W0, a consistent behavior was observed for amplitudes up to 30.0 mm, beyond which a linear increase, directly proportional to frequency, resulted in a 28.3% increment compared to rigid surfaces. Correlation analyses using Pearson linear coefficients determined relationships between structural surface vibration and pedestrian lateral motion, providing valuable insights into Structure-to-Human Interaction dynamics.

Validity Verification of Human Pose-Tracking Algorithms for Gait Analysis Capability.

Two-dimensional (2D) clinical gait analysis systems are more affordable and portable than contemporary three-dimensional (3D) clinical models. Using the Vicon 3D motion capture system as the standard, we evaluated the internal statistics of the Imasen and open-source OpenPose gait measurement systems, both designed for 2D input, to validate their output based on the similarity of results and the legitimacy of their inner statistical processes. We measured time factors, distance factors, and joint angles of the hip and knee joints in the sagittal plane while varying speeds and gaits during level walking in three in-person walking experiments under normal, maximum-speed, and tandem scenarios. The intraclass correlation coefficients of the 2D models were greater than 0.769 for all gait parameters compared with those of Vicon, except for some knee joint angles. The relative agreement was excellent for the time-distance gait parameter and moderate-to-excellent for each gait motion contraction range, except for hip joint angles. The time-distance gait parameter was high for Cronbach's alpha coefficients of 0.899-0.993 but low for 0.298-0.971. Correlation coefficients were greater than 0.571 for time-distance gait parameters but lower for joint angle parameters, particularly hip joint angles. Our study elucidates areas in which to improve 2D models for their widespread clinical application.

Improvement in Motor and Walking Capacity during Multisegmental Transcutaneous Spinal Stimulation in Individuals with Incomplete Spinal Cord Injury.

Transcutaneous multisegmental spinal cord stimulation (tSCS) has shown superior efficacy in modulating spinal locomotor circuits compared to single-site stimulation in individuals with spinal cord injury (SCI). Building on these findings, we hypothesized that administering a single session of tSCS at multiple spinal segments may yield greater enhancements in muscle strength and gait function during stimulation compared to tSCS at only one or two segments. In our study, tSCS was applied at single segments (C5, L1, and Coc1), two segments (C5-L1, C5-Coc1, and L1-Coc1), or multisegments (C5-L1-Coc1) in a randomized order. We evaluated the 6-m walking test (6MWT) and maximum voluntary contraction (MVC) and assessed the Hmax/Mmax ratio during stimulation in ten individuals with incomplete motor SCI. Our findings indicate that multisegmental tSCS improved walking time and reduced spinal cord excitability, as measured by the Hmax/Mmax ratio, similar to some single or two-site tSCS interventions. However, only multisegmental tSCS resulted in increased tibialis anterior (TA) muscle strength. These results suggest that multisegmental tSCS holds promise for enhancing walking capacity, increasing muscle strength, and altering spinal cord excitability in individuals with incomplete SCI.

Gait Features in Different Environments Contributing to Participation in Outdoor Activities in Old Age (GaitAge): Protocol for an Observational Cross-Sectional Study.

BACKGROUND: The ability to walk is a key issue for independent old age. Optimizing older peoples' opportunities for an autonomous and active life and reducing health disparities requires a better understanding of how to support independent mobility in older people. With increasing age, changes in gait parameters such as step length and cadence are common and have been shown to increase the risk of mobility decline. However, gait assessments are typically based on laboratory measures, even though walking in a laboratory environment may be significantly different from walking in outdoor environments. OBJECTIVE: This project will study alterations in biomechanical features of gait by comparing walking on a treadmill in a laboratory, level outdoor, and hilly outdoor environments. In addition, we will study the possible contribution of changes in gait between these environments to outdoor mobility among older people. METHODS: Participants of the study were recruited through senior organizations of Central Finland and the University of the Third Age, Jyväskylä. Inclusion criteria were community-dwelling, aged 70 years and older, able to walk at least 1 km without assistive devices, able to communicate, and living in central Finland. Exclusion criteria were the use of mobility devices, severe sensory deficit (vision and hearing), memory impairment (Mini-Mental State Examination ≤23), and neurological conditions (eg, stroke, Parkinson disease, and multiple sclerosis). The study protocol included 2 research visits. First, indoor measurements were conducted, including interviews (participation, health, and demographics), physical performance tests (short physical performance battery and Timed Up and Go), and motion analysis on a treadmill in the laboratory (3D Vicon and next-generation inertial measurement units [NGIMUs]). Second, outdoor walking tests were conducted, including walking on level (sports track) and hilly (uphill and downhill) terrain, while movement was monitored via NGIMUs, pressure insoles, heart rate, and video data. RESULTS: A total of 40 people (n=26, 65% women; mean age 76.3, SD 5.45 years) met the inclusion criteria and took part in the study. Data collection took place between May and September 2022. The first result is expected to be published in the spring of 2024. CONCLUSIONS: This multidisciplinary study will provide new scientific knowledge about how gait biomechanics are altered in varied environments, and how this influences opportunities to participate in outdoor activities for older people. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/52898.

The Association Between Physical Activity/Heart Rate Variability Data Obtained Using a Wearable Device and Timed Motor Functional Tests in Patients with Duchenne Muscular Dystrophy: A Pilot Study.

Background: Duchenne muscular dystrophy (DMD) is a devastating X-linked muscle disease. Clinical evaluation of DMD uses patient-intensive motor function tests, and the recent development of wearable devices allows the collection of a variety of biometric information, including physical activity. Objective: In this study, we examined differences in physical activity and heart rate variability (HRV) between patients with DMD and healthy subjects using a wearable device, and investigated any association between these parameters and motor function in patients with DMD. Methods: Participants were 7 patients with DMD and 8 healthy males, whose physical activity and HRV were provided by a wearable device. These data were used to investigate the relationship between both physical activity and HRV parameters and timed motor functional tests [Time to stand from supine, 10-meter walking time (10MWT), North Star Ambulatory Assessment (NSAA), and 6-minute walking test (6MWT)] in patients with DMD. Results: Results of 24-hours physical activity, fat burning, total number of steps and active distance, average step rate, average exercise intensity during walking, exercise, degree of forward lean during walking, maximum heart rate, normalized low frequency power (LF norm), and maximum exercise intensity in patients with DMD were lower than those in control subjects. Physical activity and HRV parameters did not correlate with the time to stand from supine. The 10MWT positively correlated with average heart rate, while NSAA negatively correlated with average heart rate, total frequency power (TF), and very low frequency power (VLF) during arousal. The 6MWT negatively correlated with ratio LF/high frequency power (HF). CONCLUSIONS: Physical activity and HRV indices that differ from those of normal children and that correlate with motor function assessment may serve as digital biomarkers.